The future of lab digitalization and automation
In this interview, Chuck Donnelly, CEO and co-founder of RockStep Solutions, discusses the significance of lab digitalization and future trends in the biotech industry.
Climb, a RockStep Solutions product, is solving the lack of informatics capabilities for in vivo researchers, especially in drug discovery. Climb streamlines in vivo study design and management, vivarium colony operations, data capture, and delivery, replacing multiple data silos with a single solution.
Donnelly describes his vision for the “lab of the future” highlighting the need for digitalization in labs, emphasizing the outdated, problematic — use of spreadsheets in in vivo research and the necessity for an informatics ecosystem to streamline data management.
Emerging technologies and scientific advancements will have a significant impact on the industry in the next decade, specifically, the role of artificial intelligence, robotics, and automation. Donnelly also points to the underutilized potential of IoT sensors predicting labs of the future will be highly automated, with sensors measuring various parameters automatically with AI algorithms processing those vast data sets.
Listen to the full interview or read the transcript to learn more.
Rebecca Willumson: Hi there. I’m Rebecca Willumson. I’m the publisher of Fierce Biotech, and I’m here today with Chuck Donnelly, CEO of RockStep Solutions. Chuck, thanks so much for joining me.
Chuck Donnelly: All right. Happy to be here and thank you for having me.
Rebecca Willumson: So before we begin, can you introduce yourself and tell me a little bit more about RockStep?
Chuck Donnelly: Sure, yeah. I’m Chuck Donnelly, CEO of RockStep Solutions, and prior to co-founding RockStep Solutions, I was Director of Computational Sciences at the Jackson Laboratory, which is a global world-class, in vivo research institution, and was funded by the National Institutes of Health. And NIH recognized this huge gap in the informatics capabilities within in vivo research, specifically drug discovery and study management. So we were tasked to develop a product which we’ve done now called Climb, which really manages the in vivo data, the operations, and the data capture as well as the data delivery. So this was an area where there was just a huge gap, a lot of spreadsheets, a lot of point solutions. So for example, we have one research organization that adopted our product and they replaced over 20 data silos with one product. So that was a big part of the problem we were solving.
Rebecca Willumson: So tell me, what are the lab of the future drivers that are creating demands for solutions like Climb?
Chuck Donnelly: Oh my, this is like the question, right? So for one thing, the Lab of the Future, we’ve been talking about it for 10 years. So 10 years ago we were talking about the Lab of the Future. We are here now in the lab of the future, but what’s surprising is that there’s still a lot of spreadsheets that are being used for managing in vivo research. And as we all know, spreadsheets are like the cockroaches of biomedical data. They just crawl all over the internet. They get emailed around, there’s no control over them. So the lab of the future is really moving into digitalization, which means all of the data are in research informatics systems, and they can be informing the decisions made in other parts of an organization. So it becomes an informatics ecosystem. And so that’s one of the drivers. And of course the artificial intelligence being ready for the future, you need to have your data and be ready for the next lab of the future, which is the next 10 years.
Rebecca Willumson: Talking more broadly, what emerging technologies or scientific advancements do you believe will have the most significant impact on the industry in the next decade?
Chuck Donnelly: Boy, another, there’s the crystal ball, right? But it’s really a great question because it’s constantly changing. Every 10 years or so, technology doubles in terms its capabilities and revolutionizes how we function. So for example, if you look, everybody’s got a smartphone, right? 10 years ago, 15 years ago, nobody had a smartphone. Now everybody, this is the way everybody is, right? So now we’re looking about the next 10 years or so. Obviously artificial intelligence is going to be a massive driver. We’re going to see a lot more robotics, a lot more automation. Also things like IOT sensors, which are out there now and they’re being used in the labs, but they’re not being fully utilized. So the lab of the future, the way I see it, will have lots of sensors measuring things automatically. So lots of automation. You have lots of artificial intelligence algorithms which are consuming the data sometimes in real time and sometimes not in real time because you’re consuming big data sets which are accumulation of lots of data over time. But that’s, to be ready for that, obviously you have to have a well-structured data system to be able to feed into that.
Rebecca Willumson: Alright, very good. Well, that’s all the questions that I have for you. Thank you so much for joining me today. I appreciate it.
Chuck Donnelly: Thank you.